面向等离子喷涂涂层质量调控的工艺优化方法研究现状  

Research on Multi-factor Parameter Optimization Methods forQuality Control of Plasma Spraying Coatings:a Review

作　　者：韩冰源[1,2] 徐文文 朱胜 黄庆伟 雷卫宁 杭卫星[1] 杜伟[1] HAN Bingyuan;XU Wenwen;ZHU Sheng;HUANG Qingwei;LEI Weining;HANG Weixing;DU Wei(School of Automotive and Traffic Engineering,Jiangsu University of Technology,Changzhou 213001,China;National Key Laboratory for Remanufacturing,Beijing 100072,China;National Key Laboratory for Human Factors Engineering,China Astronaut Research and Training Center,Beijing 100094,China)

机构地区：[1]江苏理工学院汽车与交通工程学院,常州213001 [2]再制造技术国家重点实验室,北京100072 [3]中国航天员科研训练中心,人因工程重点实验室,北京100094

出　　处：《材料导报》2021年第21期21105-21112,共8页Materials Reports

基　　金：江苏省自然科学基金(BK20191036);基础研究项目(61400040407)。

摘　　要：等离子喷涂可极大地提升零件表面耐磨、耐腐、耐高温等性能,已逐渐成为表面工程技术群的重要组成部分。等离子喷涂涂层质量受多种因素影响,因为探索涂层质量和工艺参数之间复杂且相关的映射关系对获取高质量涂层、提高喷涂效率具有重要意义。为此,本文综述了正交实验法、响应法、人工神经网络等数理统计方法在涂层质量优化领域的研究现状,总结了各类统计方法的特点及典型涂层随工艺参数的变化规律,结果表明:Ni基、Al_(2)O_(3)基等典型涂层优化后的显微硬度、结合强度等性能得到了明显提高;对Al_(2)O_(3)基涂层的不同优化实验进行比较分析,发现添加不同含量的TiO_(2)对最终的喷涂涂层性能存在一定影响。分类阐述响应曲面法中包含的不同设计方法,通过典型涂层实验分析得出:当因素个数相同且无实验点超出原定水平的危险时,BBD设计的适用范围更广。系统介绍了人工神经网络传统及改进模型在等离子喷涂涂层性能预测及优化试验中的研究情况。最后对数理统计方法在等离子喷涂涂层质量优化领域的应用现状进行了总结,并对其未来发展方向进行了一定的展望。Plasma spraying,as an important surface engineering technology,has been widely used to improve the wear resistance,corrosion resis-tance and high temperature resistance of parts.Due to the fact that the properties of plasma sprayed coating is determined by many factors,it is of great significance to investigate the complex but related mapping relationship between coating quality and process parameters for obtaining high quality coating and improving spraying efficiency.In this paper,the research status of orthogonal experiment,response method,artificial neural network and other mathematical statistical methods in the field of coating quality optimization is reviewed,and the characteristics of various statistical methods and the variation law of typical coating with process parameters are summarized.The results indicate that the micro-hardness and bonding strength of typical coatings are improved significantly after optimization,i.e.Al_(2)O_(3)coating and Ni coating,etc;the addition of TiO_(2)has a significant effect on the properties of the Al_(2)O_(3)coating;different classification methods of response surface are introduced in detail.Based on the analysis of typical coating experiments,it is concluded that BBD design is more widely used when the number of factors is the same and there is no danger that the experimental points exceed the original level;the research of traditional and improved artificial neural network mo-dels in prediction and optimization of plasma sprayed coatings are introduced.Finally,the application of mathematical statistics method in the field of plasma spraying coating quality optimization is summarized,and the future development direction is prospected.

关 键 词：等离子喷涂 参数优化 涂层性能 数理统计方法 

分 类 号：TG17[金属学及工艺—金属表面处理]